Concurrent Assessment of Sprint Running Kinematics Using Marker-Based and Markerless Motion Capture

November 6, 2025
Theia
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Summary

A July 2025 study published in the Journal of Sports Sciences evaluated the reliability of Theia3D’s markerless motion capture system for assessing lower-limb and trunk kinematics during sprint running. Researchers compared Theia3D against a marker-based optical reference system (Motion Analysis Corp. Raptor) across multiple sprint phases, including early acceleration, mid-acceleration, and top speed. Results showed good to excellent agreement between systems for most joints and movement phases, with some variability at top speed, particularly in pelvic and foot angles. The findings highlight both the promise and the challenges of measuring sprint mechanics with markerless motion capture in high-speed, real-world conditions.

Why This Matters


For coaches, biomechanists, and sports scientists, understanding sprint kinematics is essential to improving performance and preventing injuries such as hamstring strains. Traditional marker-based motion capture offers high precision but is time-consuming, costly, and challenging to deploy in real-world environments.


Markerless motion capture, especially systems like Theia3D that leverage deep learning and high-speed video data, offers a path to bring research-grade biomechanics into the field. This study represents one of the first concurrent validations of markerless and marker-based motion capture under sprint conditions, helping complete the picture of lab-based validation to justify high-speed, on-field applicability.

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Study Overview

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Objective

To compare Theia3D markerless motion capture with a gold-standard marker-based optical system (Motion Analysis Corp. Raptor) in assessing 3D sprint running kinematics across different acceleration phases.

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Participants and Setup

  • 14 physically active adults (12 male, 2 female)
  • Three sprint phases: early acceleration, mid-acceleration (~50% top speed), and maximal speed
  • Data captured simultaneously from 12 infrared (Motion Analysis Corp. Raptor, marker-based) and 8 high-speed video cameras (Qualisys Miqus, markerless) 
  • Ground reaction forces recorded via six embedded force plates

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Metrics
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Sagittal-plane joint (ankle, knee, hip) and segment (foot, shank, thigh, pelvis, trunk) angles were analyzed.

Reliability was assessed using Standard Error of Measurement (SEM) and Functional Intraclass Correlation (ICC) across full sprint gait cycles and discrete gait events (touchdown and takeoff).


Key Findings
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1. Strong Overall Agreement

  • For most joints and segments, SEM values were below 5°, indicating strong agreement between Theia3D and the marker-based system.
  • Knee, shank, and thigh angles demonstrated excellent reliability across all speeds (ICC > 0.90).

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2. High-Speed Variability

  • Differences between systems increased with speed, particularly at top speed touchdown, where ground reaction forces and soft tissue movement may amplify discrepancies.
  • This aligns with prior research showing greater inter-system variability under high dynamic load conditions.

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3. Markerless Holds Its Ground

  • Despite variability, Theia3D delivered reliable results across sprint acceleration phases, including near-top speed, an achievement typically difficult for field-based systems to deliver.
  • Researchers noted that some discrepancies could stem from limitations in both systems (e.g., marker placement errors vs. joint center estimation, model definition, etc.).

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4. Real-World Implications

  • The study reinforces Theia3D’s suitability for on-field sprint assessment and injury-prevention monitoring, especially where repeatability and efficiency outweigh sub-degree precision.
  • The authors highlight that “perfect agreement should not be the goal,” as even traditional systems face inherent limitations from soft tissue artifacts.

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What This Means for Sports Scientists and Coaches

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For biomechanists: 

Theia3D enables detailed, reliable 3D kinematic analysis of sprinting outside the lab, capturing high-speed movements without markers or extended setup. This opens the door to larger-scale studies, in-field validation, and longitudinal monitoring.

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For performance coaches:

Markerless motion capture provides actionable biomechanical feedback in training environments, helping refine sprint technique and mitigate injury risk without invasive equipment or lab access.

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For researchers: 

Theia3D’s expanding validation literature (e.g., Crespeau et al. 2025; Kanko et al. 2024; Keller et al. 2022) establishes a growing body of evidence supporting its use across speeds, clothing conditions, and movement types.
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Read the full study here. 

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Interested in Real-World Sprint Analysis?
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Want to see how Theia3D can deliver lab-quality biomechanics in field conditions? Contact us today to learn how Theia3D supports elite performance and research workflows. 

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Recent Posts
Comparing Markerless and Marker-Based Gait Kinematics in Children
A new study from Liverpool John Moores University (LJMU) compared traditional marker-based gait analysis with Theia3D’s markerless motion capture in typically developing children aged 6-13 years. The findings reinforce that markerless systems like Theia3D can deliver biomechanically meaningful data in pediatric populations while reducing preparation time and participant burden, important steps toward broader clinical adoption.
Theia3D Validated for Gait Analysis in Older Adults
Researchers from Universidade de Lisboa and KU Leuven set out to evaluate the construct validity of Theia3D markerless motion capture for 3D gait analysis in healthy community-dwelling adults aged 65 and older. Their findings offer strong support for Theia3D’s use in real-world aging populations, especially for sagittal-plane kinematics and kinetics.
Validating Theia3D for Walking and Running Gait Analysis
How accurate is markerless motion capture when gait speed changes? A new peer-reviewed study published in the Journal of Sports Sciences confirms that Theia3D can reliably capture sagittal-plane lower-limb kinematics during both walking and running at varying speeds as well as capturing kinematic responses to changes in speed, offering researchers and clinicians a validated alternative to traditional marker-based systems.
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